On Estimating the Mixed Effects Model

This paper introduces a new estimation method for time-varying individual effects in a panel data model. An important application is the estimation of time-varying technical inefficiencies of individual firms using the fixed effects model. Most models of the stochastic frontier production function require rather strong assumptions about the distribution of technical inefficiency (e.g., half-normal) and random noise (e.g., normal), and/or impose explicit restrictions on the temporal pattern of technical inefficiency. These assumptions, however, are not easily justifiable, and thus it is not clear how robust one’s results are to these assumptions. This paper drops the assumption of a prespecified model of inefficiency, and provides a semiparametric method for estimation of the time-varying effects. The methods proposed in the paper are related to principal component analysis, and estimate the time-varying effects using a small number of common functions calculated from the data. Finite sample performance of the estimators is examined via Monte Carlo simulations. We apply our methods to the analysis of technical efficiency of the U.S. banking industry. This version: August 2004. JEL Classification: C13, C14, C23, G21.